Transfer learning with false negative control improves polygenic risk prediction.

Polygenic risk score (PRS) is a quantity that aggregates the effects of variants across the genome and estimates an individual's genetic predisposition for a given trait. PRS analysis typically contains two input data sets: base data for effect size estimation and target data for individual-level prediction. Given the availability of large-scale base data, it becomes more common that the ancestral background of base and target data do not perfectly match. In this paper, we treat the GWAS summary information obtained in the base data as knowledge learned from a pre-trained model, and adopt a transfer learning framework to effectively leverage the knowledge learned from the base data that may or may not have similar ancestral background as the target samples to build prediction models for target individuals. Our proposed transfer learning framework consists of two main steps: (1) conducting false negative control (FNC) marginal screening to extract useful knowledge from the base data; and (2) performing joint model training to integrate the knowledge extracted from base data with the target training data for accurate trans-data prediction. This new approach can significantly enhance the computational and statistical efficiency of joint-model training, alleviate over-fitting, and facilitate more accurate trans-data prediction when heterogeneity level between target and base data sets is small or high.

Brugada syndrome in Japan and Europe: a genome-wide association study reveals shared genetic architecture and new risk loci.

BACKGROUND AND AIMS: Brugada syndrome (BrS) is an inherited arrhythmia with a higher disease prevalence and more lethal arrhythmic events in Asians than in Europeans. Genome-wide association studies (GWAS) have revealed its polygenic architecture mainly in European populations. The aim of this study was to identify novel BrS-associated loci and to compare allelic effects across ancestries. METHODS: A GWAS was conducted in Japanese participants, involving 940 cases and 1634 controls, followed by a cross-ancestry meta-analysis of Japanese and European GWAS (total of 3760 cases and 11 635 controls). The novel loci were characterized by fine-mapping, gene expression, and splicing quantitative trait associations in the human heart. RESULTS: The Japanese-specific GWAS identified one novel locus near ZSCAN20 (P = 1.0 × 10-8), and the cross-ancestry meta-analysis identified 17 association signals, including six novel loci. The effect directions of the 17 lead variants were consistent (94.1%; P for sign test = 2.7 × 10-4), and their allelic effects were highly correlated across ancestries (Pearson's R = .91; P = 2.9 × 10-7). The genetic risk score derived from the BrS GWAS of European ancestry was significantly associated with the risk of BrS in the Japanese population [odds ratio 2.12 (95% confidence interval 1.94-2.31); P = 1.2 × 10-61], suggesting a shared genetic architecture across ancestries. Functional characterization revealed that a lead variant in CAMK2D promotes alternative splicing, resulting in an isoform switch of calmodulin kinase II-δ, favouring a pro-inflammatory/pro-death pathway. CONCLUSIONS: This study demonstrates novel susceptibility loci implicating potentially novel pathogenesis underlying BrS. Despite differences in clinical expressivity and epidemiology, the polygenic architecture of BrS was substantially shared across ancestries.

The largest genome-wide association study for breast cancer in Taiwanese Han population.

PURPOSE: Breast cancer is a molecularly heterogeneous disease, and multiple genetic variants contribute to its development and prognosis. Most of previous genome-wide association studies (GWASs) and polygenic risk scores (PRSs) analyses focused on studying breast cancers of Caucasian populations, which may not be applicable to other population. Therefore, we conducted the largest breast cancer cohort of Taiwanese population to fill in the knowledge gap. METHODS: A total of 152,534 Participants recruited by China Medical University Hospital between 2003 and 2019 were filtered by several patient selection criteria and GWAS quality control steps, resulting in the inclusion of 2496 cases and 9984 controls for this study. We then conducted GWAS for all breast cancers and PRS analyses for all breast cancers and the four breast cancer subtypes, including luminal A, luminal B, basal-like, and HER2-enriched. RESULTS: The GWAS analyses identified 113 SNPs, 50 of which were novel. The PRS models for all breast cancers and the luminal A subtype showed positively correlated trends between the PRS and the risk of developing breast cancer. The odds ratios (95% confidence intervals) for the groups with the highest PRS in all breast cancers and the luminal A subtype were 5.33 (3.79-7.66) and 3.55 (2.13-6.14), respectively. CONCLUSION: In summary, we explored the association of genetic variants with breast cancer in the largest Taiwanese cohort and developed two PRS models that can predict the risk of developing any breast cancer and the luminal A subtype in Taiwanese women.

Evaluating clinical efficacy of hospital-based surveillance with mammography and ultrasonography for breast cancer.

Periodic mammography and/or sonography examinations are conducted across numerous hospitals nationalwidely, especially for antedees with a positive mammography screening. Despite the regular practice, clinical efficacy of hospital-based breast cancer surveillance remains unclear. Specifically, the impact of surveillance interval upon survival and prognostic surrogates stratified by menopausal status, as well as malignant transition rate should be deciphered. We retrieved cancer registry to ascertain 841 breast cancers with surveillance history through administration data. Healthy controls underwent breast surveillance and were concurrently free of cancer. More benign diseases rather than cancers were identified from premenopausal women (age ≤50 years) with sonography alone within one year, as well as older women (age >50) with both mammography and sonography one to two years before a cancer or benign diagnosis. Among breast cancers, mammography alone during the antecedent one to two years had a protective effect for diagnosing carcinoma in situ rather than invasive cancer (age-adjusted odds ratio: 0.048, P = 0.016). Three-state time homogeneous Markov model showed that hospital-based breast surveillance within 2 years of disease onset reduced the malignant transition rate by 65.16% (59.79-76.74%). The clinical efficacy of breast cancer surveillance was evidenced.

Twnbiome: a public database of the healthy Taiwanese gut microbiome.

With new advances in next generation sequencing (NGS) technology at reduced costs, research on bacterial genomes in the environment has become affordable. Compared to traditional methods, NGS provides high-throughput sequencing reads and the ability to identify many species in the microbiome that were previously unknown. Numerous bioinformatics tools and algorithms have been developed to conduct such analyses. However, in order to obtain biologically meaningful results, the researcher must select the proper tools and combine them to construct an efficient pipeline. This complex procedure may include tens of tools, each of which require correct parameter settings. Furthermore, an NGS data analysis involves multiple series of command-line tools and requires extensive computational resources, which imposes a high barrier for biologists and clinicians to conduct NGS analysis and even interpret their own data. Therefore, we established a public gut microbiome database, which we call Twnbiome, created using healthy subjects from Taiwan, with the goal of enabling microbiota research for the Taiwanese population. Twnbiome provides users with a baseline gut microbiome panel from a healthy Taiwanese cohort, which can be utilized as a reference for conducting case-control studies for a variety of diseases. It is an interactive, informative, and user-friendly database. Twnbiome additionally offers an analysis pipeline, where users can upload their data and download analyzed results. Twnbiome offers an online database which non-bioinformatics users such as clinicians and doctors can not only utilize to access a control set of data, but also analyze raw data with a few easy clicks. All results are customizable with ready-made plots and easily downloadable tables. Database URL: http://twnbiome.cgm.ntu.edu.tw/ .

Klotho Overexpression Is Frequently Associated With Upstream Rearrangements in Fusion-Negative Phosphaturic Mesenchymal Tumors of Bone and Sinonasal Tract.

Phosphaturic mesenchymal tumors (PMT) are uncommon neoplasms that cause hypophosphatemia/osteomalacia mainly by secreting fibroblast growth factor 23. We previously identified FN1::FGFR1/FGF1 fusions in nearly half of the PMTs and frequent KL (Klotho or α-Klotho) overexpression in only those with no known fusion. Here, we studied a larger cohort of PMTs for KL expression and alterations. By FN1 break-apart fluorescence in situ hybridization (FISH) and reappraisal of previous RNA sequencing data, 6 tumors previously considered "fusion-negative" (defined by negative results of FISH for FN1::FGFR1 fusion and FGF1 break-apart and/or of RNA sequencing) were reclassified as fusion-positive PMTs, including 1 containing a novel FN1::ZACN fusion. The final cohort of fusion-negative PMTs included 33 tumors from 32 patients, which occurred in the bone (n = 18), soft tissue (n = 10), sinonasal tract (n = 4), and brain (n = 1). In combination with previous work, RNA sequencing, RNA in situ hybridization, and immunohistochemistry showed largely concordant results and demonstrated KL/α-Klotho overexpression in 17 of the 28 fusion-negative and none of the 10 fusion-positive PMTs studied. Prompted by a patient in this cohort harboring germline KL upstream translocation with systemic α-Klotho overexpression and multifocal PMTs, FISH was performed and revealed KL rearrangement in 16 of the 33 fusion-negative PMTs (one also with amplification), including 14 of the 17 cases with KL/α-Klotho overexpression and none of the 11 KL/α-Klotho-low fusion-negative and 11 fusion-positive cases studied. Whole genomic sequencing confirmed translocation and inversion in 2 FISH-positive cases involving the KL upstream region, warranting further investigation into the mechanism whereby these rearrangements may lead to KL upregulation. Methylated DNA immunoprecipitation and sequencing suggested no major role of promoter methylation in KL regulation in PMT. Interestingly, KL-high/-rearranged cases seemed to form a clinicopathologically homogeneous group, showing a predilection for skeletal/sinonasal locations and typically matrix-poor, cellular solitary fibrous tumor-like morphology. Importantly, FGFR1 signaling pathways were upregulated in fusion-negative PMTs regardless of the KL status compared with non-PMT mesenchymal tumors by gene set enrichment analysis, perhaps justifying FGFR1 inhibition in treating this subset of PMTs.

High-performance deep learning pipeline predicts individuals in mixtures of DNA using sequencing data.

In this study, we proposed a deep learning (DL) model for classifying individuals from mixtures of DNA samples using 27 short tandem repeats and 94 single nucleotide polymorphisms obtained through massively parallel sequencing protocol. The model was trained/tested/validated with sequenced data from 6 individuals and then evaluated using mixtures from forensic DNA samples. The model successfully identified both the major and the minor contributors with 100% accuracy for 90 DNA mixtures, that were manually prepared by mixing sequence reads of 3 individuals at different ratios. Furthermore, the model identified 100% of the major contributors and 50-80% of the minor contributors in 20 two-sample external-mixed-samples at ratios of 1:39 and 1:9, respectively. To further demonstrate the versatility and applicability of the pipeline, we tested it on whole exome sequence data to classify subtypes of 20 breast cancer patients and achieved an area under curve of 0.85. Overall, we present, for the first time, a complete pipeline, including sequencing data processing steps and DL steps, that is applicable across different NGS platforms. We also introduced a sliding window approach, to overcome the sequence length variation problem of sequencing data, and demonstrate that it improves the model performance dramatically.

Hypoxia-responsive circular RNA circAAGAB reduces breast cancer malignancy by activating p38 MAPK and sponging miR-378 h.

BACKGROUND: Breast cancer is a prevalent disease in women, with high prevalence worldwide. The hypoxic microenvironment of solid tumors develops during the progress of carcinogenesis and leads to greater malignancy and treatment resistance. Recently, accumulating evidence indicates that non-coding RNAs, such as circular RNAs (circRNAs), play a pivotal role in altering cellular functions. However, the underlying mechanisms of circRNAs in breast cancer are still unclear. Therefore, the purpose of this study was to investigate the role of a tumor-suppressive circRNA, circAAGAB, in breast cancer by assuming down-regulation of circAAGAB under hypoxia and the properties of a tumor suppressor. METHODS: Firstly, circAAGAB was identified from expression profiling by next generation sequencing. Next, the stability of circAAGAB increased by interacting with the RNA binding protein FUS. Moreover, cellular and nuclear fractionation showed that most circAAGAB resided in the cytoplasm and that it up-regulated KIAA1522, NKX3-1, and JADE3 by sponging miR-378 h. Lastly, the functions of circAAGAB were explored by identifying its down-stream genes using Affymetrix microarrays and validated by in vitro assays. RESULTS: The results showed that circAAGAB reduced cell colony formation, cell migration, and signaling through p38 MAPK pathway, as well as increased radiosensitivity. CONCLUSION: These findings suggest that the oxygen-responsive circAAGAB acts as a tumor suppressor in breast cancer, and may contribute to the development of a more specific therapeutic regimen for breast cancer.

Radiotherapy versus low-dose tamoxifen following breast-conserving surgery for low-risk and estrogen receptor-positive breast ductal carcinoma in situ: an international open-label randomized non-inferiority trial (TBCC-ARO DCIS Trial).

BACKGROUND: Radiotherapy (RT) following breast-conserving surgery (BCS) is mainly used to decrease the rate of ipsilateral breast tumor recurrence (IBTR) in women with breast ductal carcinoma in situ (DCIS). Recent studies have demonstrated that low-dose tamoxifen significantly reduces IBTR in breast DCIS. Here, we aim to determine whether the administration of low-dose tamoxifen is non-inferior to RT in preventing IBTR in patients with low-risk characteristics of breast DCIS. METHODS/DESIGN: This is a prospective, international, open-label, randomized, non-inferiority trial. Patients with low-risk clinicopathologic features (> 40 years old, low risk of breast cancer susceptibility gene (BRCA) 1 and BRCA2 mutations, mammographically detected unicentric and non-mass lesions, low- or intermediate-grade without comedo or necrosis, measuring < 2.5 cm with margins ≥ 3 mm, and estrogen receptor-positive status) of DCIS who underwent BCS will be randomized at a 1:1 ratio to either receive tamoxifen (5 mg/day) for 5 years or undergo RT with conventional fractions (50 Gy in 25 fractions) or hypofractionations (40.05 Gy in 15 fractions). Randomization will be stratified by the Taiwan Breast Cancer Consortium. As approximately 5% of patients cannot tolerate the side effects of low-dose tamoxifen and will receive RT, we estimate that 405 patients will be randomized to a low-dose tamoxifen arm and 405 patients to the RT arm, according to a non-inferiority margin within 5% of IBTR difference and 90% ß-power noticing non-inferiority. The primary endpoints are breast tumor recurrence, including ipsilateral, regional, contralateral, and distant recurrence of breast DCIS or invasive cancer. The secondary endpoints are overall survival and adverse effects of RT and tamoxifen. Translational studies will also be conducted for this trial. DISCUSSION: This is the first non-inferiority trial on breast DCIS. This study will provide an important recommendation for clinical physicians on whether to use low-dose adjuvant tamoxifen for patients with low-risk breast DCIS who do not want to receive adjuvant RT. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT04046159, Registered on April 30, 2019.

ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets.

Competitive endogenous RNA (ceRNA) represents a novel mechanism of gene regulation that controls several biological and pathological processes. Recently, an increasing number of in silico methods have been developed to accelerate the identification of such regulatory events. However, there is still a need for a tool supporting the hypothesis that ceRNA regulatory events only occur at specific miRNA expression levels. To this end, we present an R package, ceRNAR, which allows identification and analysis of ceRNA-miRNA triplets via integration of miRNA and RNA expression data. The ceRNAR package integrates three main steps: (i) identification of ceRNA pairs based on a rank-based correlation between pairs that considers the impact of miRNA and a running sum correlation statistic, (ii) sample clustering based on gene-gene correlation by circular binary segmentation, and (iii) peak merging to identify the most relevant sample patterns. In addition, ceRNAR also provides downstream analyses of identified ceRNA-miRNA triplets, including network analysis, functional annotation, survival analysis, external validation, and integration of different tools. The performance of our proposed approach was validated through simulation studies of different scenarios. Compared with several published tools, ceRNAR was able to identify true ceRNA triplets with high sensitivity, low false-positive rates, and acceptable running time. In real data applications, the ceRNAs common to two lung cancer datasets were identified in both datasets. The bridging miRNA for one of these, the ceRNA for MAP4K3, was identified by ceRNAR as hsa-let-7c-5p. Since similar cancer subtypes do share some biological patterns, these results demonstrated that our proposed algorithm was able to identify potential ceRNA targets in real patients. In summary, ceRNAR offers a novel algorithm and a comprehensive pipeline to identify and analyze ceRNA regulation. The package is implemented in R and is available on GitHub (https://github.com/ywhsiao/ceRNAR).

Multi-ethnic Imputation System (MI-System): A genotype imputation server for high-dimensional data.

OBJECTIVE: Genotype imputation is a commonly used technique that infers un-typed variants into a study's genotype data, allowing better identification of causal variants in disease studies. However, due to overrepresentation of Caucasian studies, there's a lack of understanding of genetic basis of health-outcomes in other ethnic populations. Therefore, facilitating imputation of missing key-predictor-variants that can potentially improve a risk health-outcome prediction model, specifically for Asian ancestry, is of utmost relevance. METHODS: We aimed to construct an imputation and analysis web-platform, that primarily facilitates, but is not limited to genotype imputation on East-Asians. The goal is to provide a collaborative imputation platform for researchers in the public domain towards rapidly and efficiently conducting accurate genotype imputation. RESULTS: We present an online genotype imputation platform, Multi-ethnic Imputation System (MI-System) (https://misystem.cgm.ntu.edu.tw/), that offers users 3 established pipelines, SHAPEIT2-IMPUTE2, SHAPEIT4-IMPUTE5, and Beagle5.1 for conducting imputation analyses. In addition to 1000 Genomes and Hapmap3, a new customized Taiwan Biobank (TWB) reference panel, specifically created for Taiwanese-Chinese ancestry is provided. MI-System further offers functions to create customized reference panels to be used for imputation, conduct quality control, split whole genome data into chromosomes, and convert genome builds. CONCLUSION: Users can upload their genotype data and perform imputation with minimum effort and resources. The utility functions further can be utilized to preprocess user uploaded data with easy clicks. MI-System potentially contributes to Asian-population genetics research, while eliminating the requirement for high performing computational resources and bioinformatics expertise. It will enable an increased pace of research and provide a knowledge-base for genetic carriers of complex diseases, therefore greatly enhancing patient-driven research. STATEMENT OF SIGNIFICANCE: Multi-ethnic Imputation System (MI-System), primarily facilitates, but is not limited to, imputation on East-Asians, through 3 established prephasing-imputation pipelines, SHAPEIT2-IMPUTE2, SHAPEIT4-IMPUTE5, and Beagle5.1, where users can upload their genotype data and perform imputation and other utility functions with minimum effort and resources. A new customized Taiwan Biobank (TWB) reference panel, specifically created for Taiwanese-Chinese ancestry is provided. Utility functions include (a) create customized reference panels, (b) conduct quality control, (c) split whole genome data into chromosomes, and (d) convert genome builds. Users can also combine 2 reference panels using the system and use combined panels as reference to conduct imputation using MI-System.

High rate of postoperative upstaging of ductal carcinoma in situ when prioritizing ultrasound evaluation of mammography-detected lesions: a single-center retrospective cohort study.

BACKGROUND: The initial diagnosis of ductal carcinoma in situ (DCIS) can be upstaged to invasive cancer after definitive surgery. This study aimed to identify risk factors for DCIS upstaging using routine breast ultrasonography and mammography (MG) and to propose a prediction model. METHODS: In this single-center retrospective study, patients initially diagnosed with DCIS (January 2016-December 2017) were enrolled (final sample size = 272 lesions). Diagnostic modalities included ultrasound-guided core needle biopsy (US-CNB), MG-guided vacuum-assisted breast biopsy, and wire-localized surgical biopsy. Breast ultrasonography was routinely performed for all patients. US-CNB was prioritized for lesions visible on ultrasound. Lesions initially diagnosed as DCIS on biopsy with a final diagnosis of invasive cancer at definitive surgery were defined as "upstaged." RESULTS: The postoperative upstaging rates were 70.5%, 9.7%, and 4.8% in the US-CNB, MG-guided vacuum-assisted breast biopsy, and wire-localized surgical biopsy groups, respectively. US-CNB, ultrasonographic lesion size, and high-grade DCIS were independent predictive factors for postoperative upstaging, which were used to construct a logistic regression model. Receiver operating characteristic analysis showed good internal validation (area under the curve = 0.88). CONCLUSIONS: Supplemental screening breast ultrasonography possibly contributes to lesion stratification. The low upstaging rate for ultrasound-invisible DCIS diagnosed by MG-guided procedures suggests that it is unnecessary to perform sentinel lymph node biopsy for lesions invisible on ultrasound. Case-by-case evaluation of DCIS detected by US-CNB can help surgeons determine if repeating biopsy with vacuum-assisted breast biopsy is necessary or if sentinel lymph node biopsy should accompany breast-preserving surgery. TRIAL REGISTRATION: This single-center retrospective cohort study was conducted with the approval of the institutional review board of our hospital (approval number 201610005RIND). As this was a retrospective review of clinical data, it was not registered prospectively.

Uniportal versus multiportal nonintubated thoracoscopic anatomical resection for lung cancer: A propensity-matched analysis.

BACKGROUND/PURPOSE: No studies have compared between uniportal and multiportal nonintubated thoracoscopic anatomical resection for non-small cell lung cancer (NSCLC). We aimed to compare short- and long-term postoperative outcomes concerning these two methods. METHODS: Our retrospective dataset comprised patients with NSCLC who underwent uniportal or multiportal nonintubated thoracoscopic anatomical resection between January 2011 and December 2019. The primary outcome was recurrence-free survival. Propensity scores were matched according to age, sex, body mass index, pulmonary function, tumor size, cancer stage, and surgical method. RESULTS: In total, 1130 such patients underwent nonintubated video-assisted thoracoscopic surgery (VATS), and 490 consecutive patients with stage I-III NSCLC underwent nonintubated anatomical resection, including lobectomy and segmentectomy (uniportal, n = 158 [32.3%]; multiportal, n = 331 [67.7%]). The uniportal group had fewer dissected lymph nodes and lymph node stations. In paired group analysis, the uniportal group had shorter operation durations (99.8 vs. 138.2 min; P < 0.001), lower intensive care unit (ICU) admission rates and ICU admission intervals (7.0% vs. 27.8%; P < 0.001), and shorter postoperative hospital stays (4.1 days vs. 5.2 days; P < 0.001). The most common postoperative complication was prolonged air leaks. No surgical mortality was observed. The multiportal group had higher complication rates for grades ≥ II NSCLC; however, this difference was not significant (4.4% vs. 1.3%, respectively; P = 0.09). CONCLUSION: Nonintubated uniportal VATS for anatomical resection had better results for some perioperative outcomes than multiportal VATS. Oncological outcomes such as recurrence-free and overall survival remained uncompromised, despite fewer dissected lymph nodes.

CLIN_SKAT: an R package to conduct association analysis using functionally relevant variants.

BACKGROUND: Availability of next generation sequencing data, allows low-frequency and rare variants to be studied through strategies other than the commonly used genome-wide association studies (GWAS). Rare variants are important keys towards explaining the heritability for complex diseases that remains to be explained by common variants due to their low effect sizes. However, analysis strategies struggle to keep up with the huge amount of data at disposal therefore creating a bottleneck. This study describes CLIN_SKAT, an R package, that provides users with an easily implemented analysis pipeline with the goal of (i) extracting clinically relevant variants (both rare and common), followed by (ii) gene-based association analysis by grouping the selected variants. RESULTS: CLIN_SKAT offers four simple functions that can be used to obtain clinically relevant variants, map them to genes or gene sets, calculate weights from global healthy populations and conduct weighted case-control analysis. CLIN_SKAT introduces improvements by adding certain pre-analysis steps and customizable features to make the SKAT results clinically more meaningful. Moreover, it offers several plot functions that can be availed towards obtaining visualizations for interpretation of the analyses results. CLIN_SKAT is available on Windows/Linux/MacOS and is operative for R version 4.0.4 or later. It can be freely downloaded from https://github.com/ShihChingYu/CLIN_SKAT , installed through devtools::install_github("ShihChingYu/CLIN_SKAT", force=T) and executed by loading the package into R using library(CLIN_SKAT). All outputs (tabular and graphical) can be downloaded in simple, publishable formats. CONCLUSIONS: Statistical association analysis is often underpowered due to low sample sizes and high numbers of variants to be tested, limiting detection of causal ones. Therefore, retaining a subset of variants that are biologically meaningful seems to be a more effective strategy for identifying explainable associations while reducing the degrees of freedom. CLIN_SKAT offers users a one-stop R package that identifies disease risk variants with improved power via a series of tailor-made procedures that allows dimension reduction, by retaining functionally relevant variants, and incorporating ethnicity based priors. Furthermore, it also eliminates the requirement for high computational resources and bioinformatics expertise.

Gene-set integrative analysis of multi-omics data using tensor-based association test.

MOTIVATION: Facilitated by technological advances and the decrease in costs, it is feasible to gather subject data from several omics platforms. Each platform assesses different molecular events, and the challenge lies in efficiently analyzing these data to discover novel disease genes or mechanisms. A common strategy is to regress the outcomes on all omics variables in a gene set. However, this approach suffers from problems associated with high-dimensional inference. RESULTS: We introduce a tensor-based framework for variable-wise inference in multi-omics analysis. By accounting for the matrix structure of an individual's multi-omics data, the proposed tensor methods incorporate the relationship among omics effects, reduce the number of parameters, and boost the modeling efficiency. We derive the variable-specific tensor test and enhance computational efficiency of tensor modeling. Using simulations and data applications on the Cancer Cell Line Encyclopedia (CCLE), we demonstrate our method performs favorably over baseline methods and will be useful for gaining biological insights in multi-omics analysis. AVAILABILITY AND IMPLEMENTATION: R function and instruction are available from the authors' website: https://www4.stat.ncsu.edu/~jytzeng/Software/TR.omics/TRinstruction.pdf. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Primary Tumor Resection for Stage IV Non-small-cell Lung Cancer Without Progression After First-Line Epidermal Growth Factor Receptor-Tyrosine Kinase Inhibitor Treatment: A Retrospective Case-Control Study.

BACKGROUND: In studies of stage IV epidermal growth factor receptor (EGFR)-mutant nonsmall-cell lung cancer (NSCLC), <10% of patients underwent surgery; thus, the effect of surgery in these patients remains unclear. We investigated whether primary lung tumor resection could improve the survival of patients with stage IV EGFR-mutant NSCLC without progression after first-line EGFR-tyrosine kinase inhibitor (EGFR-TKI) treatment. METHODS: This retrospective case-control study included patients treated with first-line EGFR-TKIs without progression on follow-up imaging. Patients in the surgery group (n = 56) underwent primary tumor resection, followed by TKI maintenance therapy. Patients in the control group (n = 224; matched for age, metastatic status, and Eastern Cooperative Oncology Group performance status) received only TKI maintenance therapy. Local ablative therapy for distant metastasis was allowed in both groups. The primary endpoint was progression-free survival. The secondary endpoints were overall survival, failure patterns, and complications/adverse events. RESULTS: The median time from TKI treatment to surgery was 5.1 months. For the surgery and control groups, the median follow-up periods were 34.0 and 38.5 months, respectively, with a median (95% confidence interval) progression-free survival of 29.6 (18.9-40.3) and 13.0 (11.8-14.2) months, respectively (P < 0.001). Progression occurred in 29/56 (51.8%) and 207/224 (92.4%) patients, respectively. The median overall survival in the surgery group was not reached. The rate of surgical complications of grade ≥2 was 12.5%; complications were treated conservatively. CONCLUSIONS: Primary tumor resection is feasible for patients with EGFR-mutant nonprogressed NSCLC during first-line EGFR-TKI treatment and may improve survival better than maintenance EGFR-TKI therapy alone.

Predicting Colon Cancer-Specific Survival for the Asian Population Using National Cancer Registry Data from Taiwan.

PURPOSE: Colon cancer is the third most incident and life-threatening cancer in Taiwan. A comprehensive survival prediction system would greatly benefit clinical practice in this area. This study was designed to develop an accurate prognostic model for colon cancer patients by using clinicopathological variables obtained from the Taiwan Cancer Registry database. METHODS: We analyzed 20,218 colon cancer patients from the Taiwan Cancer Registry database, who were diagnosed between 2007 and 2015, were followed up until December 31, 2017, and had undergone curative surgery. We proposed two prognostic models, with different combinations of predictors. The first model used only traditional clinical features. The second model included several colon cancer site-specific factors (circumferential resection margin, perineural invasion, obstruction, and perforation), in addition to the traditional features. Both prediction models were developed by using a Cox proportional hazards model. Furthermore, we investigated whether race is a significant predictor of survival in colon cancer patients by using Model 1 on the Surveillance, Epidemiology, and End Results (SEER) cancer registry dataset. RESULTS: The proposed models displayed a robust prediction performance (all Harrell's c-index >0.8). For both the calibration and validation steps, the differences between the predicted and observed mortality were mostly less than 5%. CONCLUSIONS: The prediction model (Model 1) is an effective predictor of survival regardless of the ethnic background of patients and can potentially help to provide better prediction of colon cancer-specific survival outcomes, thus allowing physicians to improve treatment plans.

Distinct Survival Outcomes in Subgroups of Stage III Pancreatic Cancer Patients: Taiwan Cancer Registry and Surveillance, Epidemiology and End Results registry.

PURPOSE: Pancreatic cancer is one of the most malignant cancers with poor survival. The latest edition of the American Joint Committee on Cancer (AJCC) staging system classifies the majority of operable pancreatic cancer patients as stage-III, while dramatic heterogeneity is observed among these patients. Therefore, subgrouping is required to accurately predict their prognosis and define a treatment plan. This study conducts a cohort study to provide a more precise classification system for stage-III pancreatic cancer patients by utilizing clinical variables. METHODS: We analyzed survival using log-rank tests, univariate Cox-regression models, and Kaplan-Meier survival curves for stage-III pancreatic ductal adenocarcinoma (PDAC) patients from the Taiwan Cancer Registry (TCR). Patients were further divided into subgroups using classification and regression tree (CART) algorithm. All results were validated using the SEER database. RESULTS: Among stage-III PDAC patients, lymph node and tumor grade showed significant association with survival. Patients with N2 stage had higher mortality risks (hazard ratio [HR] = 2.30, 95% confidence interval [CI] 1.71-3.08, p < 0.0001) than N0 patients. Patients with grade 3 also had higher risk of mortality (HR = 3.80, 95% CI 2.25-6.39, p < 0.0001) than grade 1 patients. The CART algorithm stratified stage-III patients into four subgroups with significantly different survival rates. The median survival of the four subgroups was 23.5, 18.4, 14.5, and 9.0 months, respectively (p < 0.0001). Similar results were observed with SEER data. CONCLUSIONS: Lymph node involvement and tumor grade are predictive factors for survival in stage-III PDAC patients. This new precise classification system can be used to guide treatment planning in advanced-stage pancreatic cancer.

Fungal Spore Richness in School Classrooms is Related to Surrounding Forest in a Season-Dependent Manner.

Airborne fungal spores are important aeroallergens that are remarkably diverse in terms of taxonomic richness. Indoor fungal richness is dominated by outdoor fungi and is geographically patterned, but the influence of natural landscape is unclear. We aimed to elucidate the relationship between indoor fungal spore richness and natural landscape by examining the amount of surrounding forest cover. Passive sampling of airborne fungal spores was conducted in 24 schools in Taiwan during hot and cool seasons, and amplicon sequencing was used to study fungal spore (genus) richness targeting the internal transcribed spacer 2 (ITS2) region. In total, 693 fungal genera were identified, 12 of which were ubiquitous. Despite overall similarity of fungal spore richness between seasons, Basidiomycota and Ascomycota richness increased during the hot and cool seasons, respectively. Fungal spore richness in schools had a strong positive correlation with the amount of surrounding forest cover during the cool season, but not during the hot season. Fungal assemblages in schools were more similar during the hot season due to the increased ubiquity of Agaricomycetes genera. These observations indicate dispersal limitation at the kilometer scale during the cool season and increased long-distance dispersal during the hot season. Several allergenic fungi were commonly identified in schools, including some previously overlooked by conventional methods, which may be targeted as sensitizing agents in future investigations into atopic conditions. More generally, the relative importance of fungal spore richness in the development, chronicity, and severity of atopic conditions in children requires investigation.

Solid Pseudopapillary Neoplasms of the Pancreas Across Races Demonstrate Disparities with Comparably Good Prognosis.

BACKGROUND: Solid pseudopapillary neoplasms (SPNs) of the pancreas are rare with low-grade malignancy and unclarified clinicopathological features. This study aimed to examine their characteristics and re-evaluate current treatments. METHODS: Databases from three sources were screened for patients with SPNs. We compared the perioperative variables, clinical data, overall survival (OS), and prognostic factors for recurrence among the three corresponding cohorts. RESULTS: We identified 286 patients diagnosed with SPNs between 1988 and 2020. Patients were mostly women (81%; median age: 38 years), and peak incidence was observed in women of 20-29 years of age. SPNs had a peak incidence in Asian men at 50-59 years of age (p = 0.002) and a delayed peak incidence in Asian women at 30-39 years of age (p < 0.001). Treatment strategies differed significantly across the institutions and included variations in the number of harvested lymph nodes and rates of vascular resection. Lymph node positivity was the only predictor of postoperative recurrence (odds ratio, 2.2; 95% confidence interval, 1.38-2.99; p = 0.007). Higher rates of lymphovascular invasion (p = 0.02), perineural invasion (p < 0.001), and R1 margin involvement (p < 0.001), as seen in one institution, did not result in poorer long-term survival in terms of the overall (p = 0.43), SPN-specific (p = 0.69), and recurrence-free survivals (p = 0.067). CONCLUSIONS: In contrast to previous findings that SPNs are prevalent in young women, a racial predilection for middle-aged Asian men and a delayed female peak incidence were noted. Parenchyma-preserving pancreatectomy may be an acceptable treatment. Non-radical surgery may be appropriate in patients with multiple comorbidities.